Get-3D

Overview

Get-3D is a Python-based project for generating glasses-free 3D videos using depth estimation and instance segmentation techniques. It utilizes YOLOv8 for segmentation and MiDaS for depth estimation to apply depth-based effects on objects in a video.

Features

• Instance Segmentation: Uses YOLOv8 for object segmentation.
• Depth Estimation: Uses MiDaS model to estimate depth.
• 3D Effect Application: Applies zoom effects and masking to simulate 3D depth.
• Real-time Video Processing: Processes frames sequentially with a progress bar.

Methodology

The following diagram illustrates the methodology used in Get-3D:

Requirements

The required dependencies are listed in requirements.txt. Install them using:

pip install -r requirements.txt

requirements.txt

opencv-python
numpy
torch
ultralytics
torchvision
tqdm

Usage

Running the Script

Ensure the paths to your video files and models are correctly specified in the script. Then, execute the script using:

python Get-3D/script.py

Input

• A video file (e.g., wolf.mp4) that will be processed.
• Pre-trained YOLOv8 model (yolov8x-seg.pt) for instance segmentation.

Output

• A processed 3D video saved to the specified output path.

Acknowledgments

This project uses YOLOv8 from Ultralytics and MiDaS from Intel-ISL. Parts of this project page were adopted from the Nerfies page.

Website License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.